CAISEr
Comparison of Algorithms with Iterative Sample Size Estimation
Functions for performing experimental comparisons of algorithms
using adequate sample sizes for power and accuracy. Implements the
methodology originally presented in Campelo and Takahashi (2019)
CAISEr package
CAISEr: Comparing Algorithms with Iterative Sample-size Estimation in R
Author/maintainer:
- Felipe Campelo ([email protected]) [1,2]
Contributors:
- Elizabeth Wanner ([email protected])[3] (2019-)
- Fernanda Takahashi ([email protected])[2] (2016-2018)
[1] Department of Computer Science, Aston University, Birmingham UK
[2] Operations Research and Complex Systems Laboratory, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
[3] Department of Computer Science, CEFET-MG, Brazil
Implementation of R package CAISEr, with routines for automatically determining the sample size needed for performing comparative experiments with multiple algorithms on multiple problem instances.
To install the most up-to-date version directly from Github, simply type:
library(devtools)
devtools::install_github("fcampelo/CAISEr")
The most recent CRAN release of the package is also available for installation directly from the R prompt, using:
install.packages("CAISEr")
For instructions and examples of use, please take a look at the vignette
Adapting Algorithms for CAISEr, and at the package documentation, particularly
functions run_experiment(), run_nreps() and calc_instances().
Please send any bug reports, questions or suggestions directly to the package authors listed at the top of this document: https://github.com/fcampelo/CAISEr/issues